Triple

T17651267
Position Surface form Disambiguated ID Type / Status
Subject Queen Elizabeth II Highway E429494 entity
Predicate hasJunctionWith P1018 FINISHED
Object Highway 39
Highway 39 is a provincial highway in Alberta, Canada, serving as a regional connector route that intersects with major corridors such as the Queen Elizabeth II Highway.
E2286673 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Highway 39 | Statement: [Queen Elizabeth II Highway, hasJunctionWith, Highway 39]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Highway 39
Triple: [Queen Elizabeth II Highway, hasJunctionWith, Highway 39]
Generated description
Highway 39 is a provincial highway in Alberta, Canada, serving as a regional connector route that intersects with major corridors such as the Queen Elizabeth II Highway.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d889e2c2608190b762e76d9b2262f1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46e3d4948819084de72bed922be6e completed April 19, 2026, 5:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a46d45b36b88190babff0854b70f7eb completed July 2, 2026, 9:12 p.m.
NEDg Description generation batch_6a46d7d70f70819099044f0bd856950c completed July 2, 2026, 9:27 p.m.
NED2 Entity disambiguation (via description) batch_6a46d8ac9f04819096312e590e319dff completed July 2, 2026, 9:31 p.m.
Created at: April 10, 2026, 6:05 a.m.